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<li class="navelem"><a class="el" href="namespacenabu.html">nabu</a></li><li class="navelem"><b>neuralnetworks</b></li><li class="navelem"><b>models</b></li><li class="navelem"><b>model</b></li><li class="navelem"><a class="el" href="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.html">Model</a></li>  </ul>
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<a href="#pub-methods">Public Member Functions</a> &#124;
<a href="#pub-attribs">Public Attributes</a> &#124;
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<div class="title">nabu.neuralnetworks.models.model.Model Class Reference</div>  </div>
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<p>a general class for an encoder decoder system  
 <a href="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.html#details">More...</a></p>
<div class="dynheader">
Inheritance diagram for nabu.neuralnetworks.models.model.Model:</div>
<div class="dyncontent">
 <div class="center">
  <img src="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.png" usemap="#nabu.neuralnetworks.models.model.Model_map" alt=""/>
  <map id="nabu.neuralnetworks.models.model.Model_map" name="nabu.neuralnetworks.models.model.Model_map">
</map>
 </div></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a09e46f8c99f13525c31098a9e5abc55e"><td class="memItemLeft" align="right" valign="top">def&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.html#a09e46f8c99f13525c31098a9e5abc55e">__init__</a> (self, conf, trainlabels, constraint)</td></tr>
<tr class="memdesc:a09e46f8c99f13525c31098a9e5abc55e"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.html" title="a general class for an encoder decoder system ">Model</a> constructor.  <a href="#a09e46f8c99f13525c31098a9e5abc55e">More...</a><br /></td></tr>
<tr class="separator:a09e46f8c99f13525c31098a9e5abc55e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae5a09668337da15eb33f8d3120f164a9"><td class="memItemLeft" align="right" valign="top">def&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.html#ae5a09668337da15eb33f8d3120f164a9">__call__</a> (self, inputs, input_seq_length, targets, target_seq_length, is_training)</td></tr>
<tr class="memdesc:ae5a09668337da15eb33f8d3120f164a9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the neural net variables and operations to the graph.  <a href="#ae5a09668337da15eb33f8d3120f164a9">More...</a><br /></td></tr>
<tr class="separator:ae5a09668337da15eb33f8d3120f164a9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a74bcb6ff6d27ccf8980d63d34ccc92a1"><td class="memItemLeft" align="right" valign="top"><a id="a74bcb6ff6d27ccf8980d63d34ccc92a1"></a>
def&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.html#a74bcb6ff6d27ccf8980d63d34ccc92a1">variables</a> (self)</td></tr>
<tr class="memdesc:a74bcb6ff6d27ccf8980d63d34ccc92a1"><td class="mdescLeft">&#160;</td><td class="mdescRight">get a list of the models's variables <br /></td></tr>
<tr class="separator:a74bcb6ff6d27ccf8980d63d34ccc92a1"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-attribs"></a>
Public Attributes</h2></td></tr>
<tr class="memitem:ae32bb505a189b7b6babbc685eab98b60"><td class="memItemLeft" align="right" valign="top"><a id="ae32bb505a189b7b6babbc685eab98b60"></a>
&#160;</td><td class="memItemRight" valign="bottom"><b>conf</b></td></tr>
<tr class="separator:ae32bb505a189b7b6babbc685eab98b60"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4f513446e46d1ce4719188cbe007c100"><td class="memItemLeft" align="right" valign="top"><a id="a4f513446e46d1ce4719188cbe007c100"></a>
&#160;</td><td class="memItemRight" valign="bottom"><b>input_names</b></td></tr>
<tr class="separator:a4f513446e46d1ce4719188cbe007c100"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a57bcc5b0fe6fc50233efde6750cbf674"><td class="memItemLeft" align="right" valign="top"><a id="a57bcc5b0fe6fc50233efde6750cbf674"></a>
&#160;</td><td class="memItemRight" valign="bottom"><b>output_names</b></td></tr>
<tr class="separator:a57bcc5b0fe6fc50233efde6750cbf674"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a17b8c89bf6f0a619f37fe86f0f77253e"><td class="memItemLeft" align="right" valign="top"><a id="a17b8c89bf6f0a619f37fe86f0f77253e"></a>
&#160;</td><td class="memItemRight" valign="bottom"><b>output_dims</b></td></tr>
<tr class="separator:a17b8c89bf6f0a619f37fe86f0f77253e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acbb571ec2af88efc3cf2464a3052fffc"><td class="memItemLeft" align="right" valign="top"><a id="acbb571ec2af88efc3cf2464a3052fffc"></a>
&#160;</td><td class="memItemRight" valign="bottom"><b>encoder</b></td></tr>
<tr class="separator:acbb571ec2af88efc3cf2464a3052fffc"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5362e5acd1d8b726e55ce7acc13ec691"><td class="memItemLeft" align="right" valign="top"><a id="a5362e5acd1d8b726e55ce7acc13ec691"></a>
&#160;</td><td class="memItemRight" valign="bottom"><b>decoder</b></td></tr>
<tr class="separator:a5362e5acd1d8b726e55ce7acc13ec691"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>a general class for an encoder decoder system </p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a09e46f8c99f13525c31098a9e5abc55e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a09e46f8c99f13525c31098a9e5abc55e">&sect;&nbsp;</a></span>__init__()</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">def nabu.neuralnetworks.models.model.Model.__init__ </td>
          <td>(</td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>self</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>conf</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>trainlabels</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>constraint</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p><a class="el" href="classnabu_1_1neuralnetworks_1_1models_1_1model_1_1Model.html" title="a general class for an encoder decoder system ">Model</a> constructor. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">conf</td><td>The model configuration as a configparser object </td></tr>
    <tr><td class="paramname">trainlabels</td><td>the number of extra labels required by the trainer </td></tr>
    <tr><td class="paramname">constraint</td><td>a constraint for the model paramaters </td></tr>
  </table>
  </dd>
</dl>

</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a id="ae5a09668337da15eb33f8d3120f164a9"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ae5a09668337da15eb33f8d3120f164a9">&sect;&nbsp;</a></span>__call__()</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">def nabu.neuralnetworks.models.model.Model.__call__ </td>
          <td>(</td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>self</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>inputs</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>input_seq_length</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>targets</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>target_seq_length</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">&#160;</td>
          <td class="paramname"><em>is_training</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Add the neural net variables and operations to the graph. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">inputs</td><td>the inputs to the neural network, this is a dictionary of [batch_size x time x ...] tensors </td></tr>
    <tr><td class="paramname">input_seq_length</td><td>The sequence lengths of the input utterances, this is a dictionary of [batch_size] vectors </td></tr>
    <tr><td class="paramname">targets</td><td>the targets to the neural network, this is a dictionary of [batch_size x time x ...] tensors. </td></tr>
    <tr><td class="paramname">target_seq_length</td><td>The sequence lengths of the target utterances, this is a dictionary of [batch_size] vectors </td></tr>
    <tr><td class="paramname">is_training</td><td>whether or not the network is in training mode</td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd><ul>
<li>output logits, which is a dictionary of [batch_size x time x ...] </li>
</ul>
</dd>
<dd>
tensors<ul>
<li>the output logits sequence lengths which is a dictionary of [batch_size] vectors </li>
</ul>
</dd></dl>

</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li><a class="el" href="model_8py.html">model.py</a></li>
</ul>
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